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rOpenSci - open tools for open science

rOpenSci - open tools for open science
Open Tools and R Packages for Open Science
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Published
Author Shaun Wilkinson

Evolutionary biologists are increasingly using R for building,editing and visualizing phylogenetic trees.The reproducible code-based workflow and comprehensive array of toolsavailable in packages such as ape,phangorn andphytools make R an ideal platform forphylogenetic analysis.Yet the many different tree formats are not well integrated,as pointed out in a recentpost.

Published
Authors Monica Gerber, Jennifer Thompson, Jenny Draper, Kyle Hamilton, Charles T. Gray

It’s easy to come to a conference and feel intimidated by the wealth of knowledge and expertise of other attendees. As Ellen Ullman, a software engineer and writer describes, One of the best ways to start feeling less intimidated is to start talking to others. Ullman continues, At rOpenSci unconf18, we learned that it’s ok to feel like you don’t know everything – indeed, that’s how just about everyone feels!

Published
Authors Amanda Dobbyn, Jim Hester, Laura DeCicco, Christine Stawitz, Isabella Velasquez

Data == knowledge! Much of the data we use, whether it be fromgovernment repositories, social media, GitHub, or e-commerce sites comesfrom public-facing APIs. The quantity of data available is trulystaggering, but munging JSON output into a format that is easilyanalyzable in R is an equally staggering undertaking.

Published
Author Jorge Cimentada

Introduction I never thought that I’d be programming software in my career. I startedusing R a little over 2 years now and it’s been one of the most importantdecisions in my career. Secluded in a small academic office with no oneto discuss/interact about my new hobby, I started searching the web fortutorials and packages. After getting to know how amazing and nurturingthe R community is, it made me want to become a data scientist.

Published
Author Jeroen Ooms

Have you ever needed to connect to a remote server over SSH to transfer files via SCP or to setup a secure tunnel, and wished you could do so from R itself? The new rOpenSci ssh package provides a native ssh client in R allows you to do that and even more, like running a command or script on the host while streaming stdout and stderr directly to the client. The package is based on libssh, a powerful C library implementing the SSH protocol.

Published

The drake R package is not only a reproducible research solution, but also a serious high-performance computing engine. The package website introduces drake, and this technical note draws from the guides on high-performance computing and timing in the drake manual. You can help! Some of these features are brand new, and others are newly refactored.

Published
Author Guangchuang Yu

Phylogenetic trees are commonly used to present evolutionary relationships of species. Newick is the de facto format in phylogenetic for representing tree(s). Nexus format incorporates Newick tree text with related information organized into separated units known as blocks. For the R community, we have ape and phylobase packages to import trees from Newick and Nexus formats.

Published
Author Evan Odell

I’m excited to announce a new package for accessing official statistics from the UK. nomisr is the R client for the Nomis database. Nomis is run by Durham University on behalf of the UK’s Office for National Statistics (ONS), and contains over a thousand datasets, primarily on the UK labour market, census data, benefit spending and general economic activity.

Published
Author Sasha Goodman

The Apache Tika parser is like the Babel fish in Douglas Adam’s book, “The Hitchhikers’ Guide to the Galaxy” 1 . The Babel fish translates any natural language to any other. Although Tika does not yet translate natural language, it starts to tame the tower of babel of digital document formats. As the Babel fish allowed a person to understand Vogon poetry, Tika allows an analyst to extract text and objects from Microsoft Word.

Published
Author Amanda Dobbyn

library(tidyverse)library(monkeylearn) This is a story (mostly) about how I started contributing to the rOpenSci package monkeylearn. I can’t promise any life flipturning upside down, but there will be a small discussion about git best practices which is almost as good 🤓. The tl;dr here is nothing novel but is something I wish I’d experienced firsthand sooner.